Calculate multilple stats for two or more columns in R data.table

By total coincidence I was working today on a helper function callsacross that does exactly what you want. It pairs with the env programming mechanism in recent versions of {data.table}.

library(data.table)
set.seed(1) # please use a seed for reproducibility!!!
dt                                 
#> 1:      a          11           1         120          40
#> 2:      b          12           2         110          10
#> 3:      c          10           5          90          30

dt[, j, by=class, env=list(j=query), verbose=TRUE]
#> Argument 'by' after substitute: class
#> Argument 'j' after substitute: list(val1maximo = max(val1, na.rm = TRUE), val1minimo = min(val1, na.rm = TRUE), val2maximo = max(val2, na.rm = TRUE), val2minimo = min(val2, na.rm = TRUE))
#> [...]
#> GForce optimized j to 'list(gmax(val1, na.rm = TRUE), gmin(val1, na.rm = TRUE), gmax(val2, na.rm = TRUE), gmin(val2, na.rm = TRUE))' (see ?GForce)
#> Making each group and running j (GForce TRUE) ...
#> [...]

callsacross 

An alternative where the function takes "all columns" (instead of individual columns).

stats2  setNames(paste0(nm, c("maximo", "minimo")))
  }, frm, names(frm)) |>
  unname() |>
  do.call(cbind.data.frame, args = )
}
dt[, stats2(.SD), by = class, .SDcols = c('val1', 'val2')]
    class val1maximo val1minimo val2maximo val2_minimo
                               
1:      a           9           1         120          30
2:      b          11           2          90          10
3:      c          12           4         110          50

Reproducible data:

set.seed(42)
dt 

You need to modify stats to accept an array (one column per numeric variable) and return a simple list (not a list of lists). Keeping everything as lists (instead of arrays or matrices) within stats will preserve the names needed to identify the columns.

stats